How AI market research works and what ad­vant­ages it offers

AI market research uses ar­ti­fi­cial in­tel­li­gence to gain insights into relevant markets, market segments, trends and customer behaviour. By using AI tech­no­lo­gies, large amounts of data can be analysed more quickly and more precise pre­dic­tions can be made, which creates com­pet­it­ive ad­vant­ages and fa­cil­it­ates strategic decisions.

What is AI market research?

Tra­di­tion­al market research is a subset of marketing research that con­cen­trates on gathering, analysing, and in­ter­pret­ing in­form­a­tion about market con­di­tions and emerging trends. By sys­tem­at­ic­ally exploring relevant sub­mar­kets, busi­nesses can make well-informed decisions, gain a deeper un­der­stand­ing of their target audience and com­pet­it­ors, and identify market trends at an early stage. AI market research extends this process through the use of ar­ti­fi­cial in­tel­li­gence tech­no­lo­gies. The aim is to process and evaluate data faster and more precisely and to make new cor­rel­a­tions visible. Various tech­no­lo­gies are used for this purpose:

• Machine learning (ML) aims to enable computer systems to learn in­de­pend­ently and con­tinu­ously improve with the help of large amounts of data.
• Natural language pro­cessing (NLP) enables AI tech­no­lo­gies to recognise, un­der­stand and generate human language.
• Computer vision enables al­gorithms to extract in­form­a­tion from images.
• Pre­dict­ive analytics uses stat­ist­ic­al models and his­tor­ic­al data to forecast future results or de­vel­op­ments.

To date, market research with AI tech­no­lo­gies has primarily been used to provide decision makers with valid re­com­mend­a­tions for action. However, in­ter­pret­ing the results and deriving decisions is still largely the re­spons­ib­il­ity of humans.

What ad­vant­ages does AI market research offer?

The use of ar­ti­fi­cial in­tel­li­gence in market research offers numerous ad­vant­ages that clearly surpass tra­di­tion­al methods. The most important ad­vant­ages of market analysis using AI tools are as follows:

• Faster data pro­cessing: AI systems are capable of analysing large amounts of data in a very short time, which speeds up the market research process con­sid­er­ably. Instead of weeks of manual analysis, results are usually available very quickly.
• Greater precision: Sources of error can be minimised through the use of advanced al­gorithms. AI re­cog­nises patterns, trends and complex re­la­tion­ships that may be over­looked by manual analysis. In addition, AI models learn from his­tor­ic­al data, con­tinu­ously in­creas­ing their pre­dict­ive accuracy.
• Auto­ma­tion of recurring tasks: AI market research offers the op­por­tun­ity to automate stand­ard­ised processes, such as col­lect­ing and sorting data or creating reports. As a result, workloads are reduced, allowing employees to focus on more strategic tasks.
• Cus­tom­ised analyses: Once the AI system has been trained, it can be applied to different data volumes and market segments. AI market analyses provide companies with cus­tom­ised results that are tailored to their in­di­vidu­al needs.

Companies can use AI in market research to secure com­pet­it­ive ad­vant­ages by con­duct­ing market analyses and com­pet­it­or analyses more ef­fi­ciently and precisely. The auto­ma­tion of many processes can also reduce costs in the long term.

How to conduct market research with AI

An AI-supported market analysis requires a struc­tured and well thought-out approach. The following step-by-step guide will show you how to proceed in order to exploit the potential of ar­ti­fi­cial in­tel­li­gence in market research:

1. Define ob­ject­ives and re­quire­ments: Market research aims to answer questions relating to marketing. Therefore, it’s necessary to first define a problem and set clear ob­ject­ives. Classic AI market research topics include identi­fy­ing in­ter­est­ing target groups for a new product, analysing trends and com­pet­it­or analyses.
2. Define research design: The next step involves defining the in­form­a­tion re­quire­ments and selecting an ap­pro­pri­ate study design. The key focus is on de­term­in­ing how to gather the necessary data. This process includes identi­fy­ing the target group, selecting the survey method, and pin­point­ing relevant data sources.
3. Choosing the AI tool: There are now numerous AI ap­plic­a­tions that are suitable for market research. Choose a tool that fits your re­quire­ments and offers the functions you need, such as text analysis and pattern re­cog­ni­tion. When choosing, also consider ease of use, scalab­il­ity and com­pat­ib­il­ity with existing systems to maximise the benefits.
4. Collect and process data: Collect relevant data from various sources, such as customer surveys and feedback, social media analyses or sales stat­ist­ics, to generate a com­pre­hens­ive database. As raw data is often incorrect or contains in­com­plete in­form­a­tion, it’s advisable to cleanse and structure it to ensure high data quality.
5. Data analysis: Have the collected data analysed by the selected AI tool to identify patterns and cor­rel­a­tions or predict future trends. Thanks to machine learning al­gorithms, the quality of AI-supported data analyses and forecasts is con­stantly improving.
6. Interpret results and derive re­com­mend­a­tions for action: Analyse the results and prepare the data visually to make it ac­cess­ible. Use the insights gained to plan specific measures, such as de­vel­op­ing new products or adapting the marketing strategy.

Use cases for AI market research

AI market research opens up a wide range of possible ap­plic­a­tions. Here are some areas of ap­plic­a­tion with specific practical examples:

• Target group analysis: A beverage brand has developed a new product and is using AI to analyse data sets from customer surveys and social media to identify relevant target groups for its new drink.
• Trend analysis: A fashion company uses computer vision to identify the colour and style trends of the coming season by analysing images from social networks.
• Com­pet­it­or analysis: With the help of AI tools, a company from the auto­mot­ive industry scans online reviews, price de­vel­op­ments and marketing activ­it­ies of com­pet­it­ors in real time in order to strengthen its own market position.
• Product de­vel­op­ment: An elec­tron­ics company uses AI tools to analyse customer reviews and support requests to improve product design.
• Stock market: AI al­gorithms are used by asset man­age­ment companies to predict future price movements based on a variety of in­dic­at­ors, such as financial news and price data.
• Real estate market: Real estate agents use AI market research for location analyses in order to better assess prices and demand.